{"id":27462,"date":"2020-07-06T05:59:35","date_gmt":"2020-07-06T05:59:35","guid":{"rendered":"https:\/\/www.inspirenignite.com\/anna-university\/big-data-analytics-cc-7th-sem-syllabus-for-be-2017-regulation-anna-univ-professional-elective-ii\/"},"modified":"2020-07-06T05:59:35","modified_gmt":"2020-07-06T05:59:35","slug":"big-data-analytics-cc-7th-sem-syllabus-for-be-2017-regulation-anna-univ-professional-elective-ii","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/anna-university\/big-data-analytics-cc-7th-sem-syllabus-for-be-2017-regulation-anna-univ-professional-elective-ii\/","title":{"rendered":"Big Data Analytics C&amp;C 7th Sem Syllabus for BE 2017 Regulation Anna Univ (Professional Elective II)"},"content":{"rendered":"<p>Big Data Analytics C&amp;C 7th Sem Syllabus for BE 2017 Regulation Anna Univ (Professional Elective II) detail syllabus for Computer &amp; Communication Engineering (C&amp;C), 2017 regulation is collected from the <a href=\"https:\/\/www.annauniv.edu\/\" target=\"_blank\" rel=\"noopener\">Anna Univ<\/a> official website and presented for students of Anna University. The details of the course are: course code (CS8091), Category (PE), Contact Periods\/week (3), Teaching hours\/week (3), Practical Hours\/week (0). The total course credits are given in combined syllabus.<\/p>\n<p>For all other c&amp;c 7th sem syllabus for be 2017 regulation anna univ you can visit <a href=\"..\/cc-7th-sem-syllabus-for-be-2017-regulation-anna-univ\">C&amp;C 7th Sem syllabus for BE 2017 regulation Anna Univ Subjects<\/a>. For all other Professional Elective II subjects do refer to <a href=\"..\/professional-elective-ii-cc-7th-sem-syllabus-for-be-2017-regulation-anna-univ\">Professional Elective II<\/a>. The detail syllabus for big data analytics is as follows.<\/p>\n<p><h4>Course Objective:<\/h4>\n<ul>\n<li>To know the fundamental concepts of big data and analytics.<\/li>\n<li>To explore tools and practices for working with big data<\/li>\n<li>To learn about stream computing.<\/li>\n<li>To know about the research that requires the integration of large amounts of data.<\/li>\n<\/ul>\n<p><h4>Unit I<\/h4>\n<p>For complete syllabus and results, class timetable and more pls <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">download iStudy<\/a>. Its a light weight, easy to use, no images, no pdfs platform to make students life easier.<\/p>\n<p><h4>Unit II<\/h4>\n<p><strong>Clustering and Classification<\/strong><br \/>\nAdvanced Analytical Theory and Methods: Overview of Clustering &#8211; K-means &#8211; Use Cases &#8211; Overview of the Method &#8211; Determining the Number of Clusters &#8211; Diagnostics &#8211; Reasons to Choose and Cautions .Classification: Decision Trees &#8211; Overview of a Decision Tree &#8211; The General Algorithm &#8211; Decision Tree Algorithms &#8211; Evaluating a Decision Tree &#8211; Decision Trees in R &#8211; Naive Bayes &#8211; Bayes Theorem -Naive Bayes Classifier.\n<\/p>\n<p><h4>Unit III<\/h4>\n<p><strong>Association and Recommendation System<\/strong><br \/>\nAdvanced Analytical Theory and Methods: Association Rules &#8211; Overview &#8211; Apriori Algorithm &#8211; Evaluation of Candidate Rules &#8211; Applications of Association Rules &#8211; Finding Association&amp; finding similarity -Recommendation System: Collaborative Recommendation- Content Based Recommendation -Knowledge Based Recommendation- Hybrid Recommendation Approaches.\n<\/p>\n<p><h4>Unit IV<\/h4>\n<p>For complete syllabus and results, class timetable and more pls <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">download iStudy<\/a>. Its a light weight, easy to use, no images, no pdfs platform to make students life easier.<\/p>\n<p><h4>Unit V<\/h4>\n<p><strong>Nosql Data Management for Big Data and Visualization<\/strong><br \/>\nNoSQL Databases : Schema-less Models: Increasing Flexibility for Data Manipulation-Key Value Stores- Document Stores &#8211; Tabular Stores &#8211; Object Data Stores &#8211; Graph Databases Hive &#8211; Sharding &#8211;Hbase &#8211; Analyzing big data with twitter &#8211; Big data for E-Commerce Big data for blogs &#8211; Review of Basic Data Analytic Methods using R.\n<\/p>\n<p><h4>Course Outcome:<\/h4>\n<p>Upon completion of the course, the students will be able to:<\/p>\n<ul>\n<li>Work with big data tools and its analysis techniques<\/li>\n<li>Analyze data by utilizing clustering and classification algorithms<\/li>\n<li>Learn and apply different mining algorithms and recommendation systems for large volumes of data<\/li>\n<li>Perform analytics on data streams<\/li>\n<li>Learn NoSQL databases and management.<\/li>\n<\/ul>\n<p><h4>Text Books:<\/h4>\n<ol>\n<li>Anand Rajaraman and Jeffrey David Ullman, &#8220;Mining of Massive Datasets&#8221;, Cambridge University Press, 2012.<\/li>\n<li>David Loshin, &#8220;Big Data Analytics: From Strategic Planning to Enterprise Integration with Tools, Techniques, NoSQL, and Graph&#8221;, Morgan Kaufmann\/El sevier Publishers, 2013.<\/li>\n<\/ol>\n<p><h4>References:<\/h4>\n<ol>\n<li>EMC Education Services, &#8220;Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data&#8221;, Wiley publishers, 2015.<\/li>\n<li>Bart Baesens, &#8220;Analytics in a Big Data World: The Essential Guide to Data Science and its Applications&#8221;, Wiley Publishers, 2015.<\/li>\n<li>Dietmar Jannach and Markus Zanker, &#8220;Recommender Systems: An Introduction&#8221;, Cambridge University Press, 2010.<\/li>\n<li>Kim H. Pries and Robert Dunnigan, &#8220;Big Data Analytics: A Practical Guide for Managers &#8221; CRC Press, 2015.<\/li>\n<li>Jimmy Lin and Chris Dyer, &#8220;Data-Intensive Text Processing with MapReduce&#8221;, Synthesis Lectures on Human Language Technologies, Vol. 3, No. 1, Pages 1-177, Morgan Claypool publishers, 2010.<\/li>\n<\/li>\n<\/ol>\n<p>For detail syllabus of all other subjects of BE C&amp;C, 2017 regulation do visit <a href=\"..\/category\/cc+7th-sem\">C&amp;C 7th Sem syllabus for 2017 Regulation<\/a>.<\/p>\n<p>Dont forget to <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">download iStudy<\/a> for latest syllabus and results, class timetable and more.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Big Data Analytics C&amp;C 7th Sem Syllabus for BE 2017 Regulation Anna Univ (Professional Elective II) detail syllabus for Computer &amp; Communication Engineering (C&amp;C), 2017 regulation is collected from the [&hellip;]<\/p>\n","protected":false},"author":2297,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"footnotes":""},"categories":[50,68],"tags":[],"class_list":["post-27462","post","type-post","status-publish","format-standard","hentry","category-7th-sem","category-cc"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/27462","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/users\/2297"}],"replies":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/comments?post=27462"}],"version-history":[{"count":0,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/27462\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/media?parent=27462"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/categories?post=27462"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/tags?post=27462"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}